Multi-dimensional Evaluation Method Research Articles

Affective product form bionic design based on functional analysis

To address the challenge of the absence of automated design and evaluation methods encompassing both functional and emotional analysis in product form bionic design (PFBD), this study introduces a novel affective PFBD method based on functional analysis. Firstly, the target product, target emotion and target creature are identified through questionnaire surveys and statistical analysis. Elliptical Fourier analysis and principal component analysis are employed to parameterize the shape outlines of the target products and creature, yielding principal component score data capturing their shape features. Secondly, product form and biological shape are fused by utilizing a proposed fusion generation operator to generate diverse PFBD conceptual schemes. Finally, a comprehensive multi-dimensional evaluation method, incorporating the functional analysis model, bionic evaluation model and emotional evaluation model, is formulated to assess the conceptual schemes and identify the optimal scheme. To validate the feasibility and effectiveness of the proposed method, it is applied to the automated generative design and evaluation of water cup shapes. The outcome reveals the identification of an optimal solution that not only satisfies the functional requirements of the product but also addresses user emotional needs. The results underscore the method's outstanding performance in PFBD involving both functional and emotional analysis, establishing it as an effective tool for designers to efficiently generate a variety of solutions, thereby ensuring the rationality and scientific foundation of product design.

Multidimensional Evaluation Methods for Deep Learning Models in Target Detection for SAR Images

As artificial intelligence technology advances, the application of object detection technology in the field of SAR (synthetic aperture radar) imagery is becoming increasingly widespread. However, it also faces challenges such as resource limitations in spaceborne environments and significant uncertainty in the intensity of interference in application scenarios. These factors make the performance evaluation of object detection key to ensuring the smooth execution of tasks. In the face of such complex and harsh application scenarios, methods that rely on single-dimensional evaluation to assess models have had their limitations highlighted. Therefore, this paper proposes a multi-dimensional evaluation method for deep learning models used in SAR image object detection. This method evaluates models in a multi-dimensional manner, covering the training, testing, and application stages of the model, and constructs a multi-dimensional evaluation index system. The training stage includes assessing training efficiency and the impact of training samples; the testing stage includes model performance evaluation, application-based evaluation, and task-based evaluation; and the application stage includes model operation evaluation and model deployment evaluation. The evaluations of these three stages constitute the key links in the performance evaluation of deep learning models. Furthermore, this paper proposes a multi-indicator comprehensive evaluation method based on entropy weight correlation scaling, which calculates the weights of each evaluation indicator through test data, thereby providing a balanced and comprehensive evaluation mechanism for model performance. In the experiments, we designed specific interferences for SAR images in the testing stage and tested three models from the YOLO series. Finally, we constructed a multi-dimensional performance profile diagram for deep learning object detection models, providing a new visualization method to comprehensively characterize model performance in complex application scenarios. This can provide more accurate and comprehensive model performance evaluation for remote sensing data processing, thereby guiding model selection and optimization. The evaluation method proposed in this study adopts a multi-dimensional perspective, comprehensively assessing the three core stages of a model’s lifecycle: training, testing, and application. This framework demonstrates significant versatility and adaptability, enabling it to transcend the boundaries of remote sensing technology and provide support for a wide range of model evaluation and optimization tasks.

Study on the quality of Corydalis Rhizoma in Zhejiang based on multidimensional evaluation method

Ethnopharmacological relevanceThe quality requirements of Corydalis Rhizoma (CR) in different producing areas are uniform, resulting in uneven efficacy. As a genuine producing area, the effective quality control of CR in Zhejiang Province (ZJ) could provide a theoretical basis for the rational application of medicinal materials. Aim of the studyThe purpose of this study was to effectively distinguish the CR inside and outside ZJ, and provided a theoretical basis for the quality control and material basis research of ZJ CR. Materials and methodsThe core components of ZJ CR could be identified by HPLC combined with chemometrics screening, and the quality of CR from different producing areas was evaluated by a genetic algorithm-back propagation (GA-BP) neural network. Chromaticity and near-infrared (NIR) spectroscopy were used to identify CR inside and outside ZJ, and rapid content prediction was realized. The analgesic effect of CR in different regions was compared by a zebrafish analgesic experiment. Analgesic experiments in rats and analysis of the research status of quality components were used to screen the quality control components of ZJ CR. ResultsThe contents of palmatine hydrochloride (YSBMT), dehydrocorydaline (TQZJJ), tetrahydropalmatine (YHSYS), tetrahydroberberine (SQXBJ), corydaline (YHSJS), stylopine (SQHLJ), and isoimperatorin (YOQHS) in ZJ CR were higher than those in CR from outside ZJ, but the content of protopine (YAPJ) and berberine hydrochloride (YSXBJ) was lower than that in CR from outside ZJ. YHSJS and SQHLJ could be used as the core components to identify ZJ CR. The GA-BP neural network showed that the relative importance of ZJ CR was the strongest. Chroma-content correlation analysis and the NIR qualitative model could effectively distinguish CR from inside and outside of ZJ, and the NIR quantitative model could quickly predict the content of CR from inside and outside of ZJ. Zebrafish experiments showed that ZJ, Shaanxi (SX), Henan (HN), and Sichuan (SC) CR had significant analgesic effects, while Hebei (HB) CR had no significant analgesic effect. Overall comparison, the analgesic effect of ZJ CR was better than that of CR outside ZJ. The comprehensive score of the grey correlation degree between YAPJ, YSBMT, YSXBJ, TQZJJ, YHSYS, YHSJS, SQXBJ, and SQHLJ were higher than 0.9, and the research frequency were extremely high. ConclusionsThe relative importance of the content and origin of most components of ZJ CR was higher than that of CR outside ZJ. The holistic analgesic effect of ZJ CR was better than that of CR outside ZJ, but slightly lower than that of SX CR. YHSJS and SQHLJ could be used as the core components to identify ZJ CR. YAPJ, YSBMT, YSXBJ, TQZJJ, YHSYS, SQXBJ, YHSJS, and SQHLJ could be used as the quality control components of ZJ CR. The multidimensional evaluation method used in this study provided a reference for the quality control and material basis research of ZJ CR.

An evaluation of Astragali Radix with different growth patterns and years, based on a new multidimensional comparison method.

With the depletion of wild Astragali Radix (WA) resources, imitated-wild Astragali Radix (IWA) and cultivated Astragali Radix (CA) have become the main products of Astragali Radix. However, the quality differences of three growth patterns (WA, IWA, CA) and different growth years of Astragali Radix have not been fully characterized, leading to a lack of necessary scientific evidence for their use as substitutes for WA. We innovatively proposed a multidimensional evaluation method that encompassed traits, microstructure, cell wall components, saccharides, and pharmacodynamic compounds, to comprehensively explain the quality variances among different growth patterns and years of Astragali Radix. Our study showed that the quality of IWA and WA was comparatively similar, including evaluation indicators such as apparent color, sectional structure and odor, thickness of phellem, diameter and number of vessels, morphology of phloem and xylem, and the levels and ratios of cellulose, hemicellulose, lignin, sucrose, starch, water-soluble polysaccharides, total-saponins. However, the content of sucrose, starch and sorbose in CA was significantly higher than WA, and the diameter and number of vessels, total-flavonoids content were lower than WA, indicating significant quality differences between CA and WA. Hence, we suggest that IWA should be used as a substitute for WA instead of CA. As for the planting years of IWA, our results indicated that IWA aged 1-32 years could be divided into three stages according to their quality change: rapid growth period (1-5 years), stable growth period (6-20 years), and elderly growth period (25-32 years). Among these, 6-20 years old IWA exhibited consistent multidimensional comparative results, showcasing elevated levels of key active components such as water-soluble polysaccharides, flavonoids, and saponins. Considering both the quality and cultivation expenses of IWA, we recommend a cultivation duration of 6-8 years for growers. In conclusion, we established a novel multidimensional evaluation method to systematically characterize the quality of Astragali Radix, and provided a new scientific perspective for the artificial cultivation and quality assurance of Astragali Radix.

Research on multi-dimensional evaluation method of sports interest of college students

Abstract This study investigates students’ engagement with sports content, employing a novel method to quantify interest levels through observable physical responses. By analyzing facial expressions and body language, specifically the muscle activities across various body parts, we derive a unique numerical value to represent the intensity of pleasure experienced by viewers in each frame. This approach involves calculating the rotational angle weights between limbs and their movements over consecutive frames, leading to a comprehensive evaluation score for the observed actions. Utilizing the Openpose platform for data analysis, we discovered a significant correlation (r=0.43) between real-time assessment scores and the “sports participation” interest dimension. Analysis of facial expressions in educational sports videos revealed “concentration” as the predominant expression, indicating high student interest. Furthermore, the study identified instances of interest fatigue within an 18-minute duration, notably between frames 32005 and 36507, with a PERCLO value of 0.46, demonstrating the method’s potential in assessing and enhancing engagement with sports education.

Evaluating multi-dimensional response capability of electric bus considering carbon emissions and traffic index

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified.

Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring

IntroductionArtificial intelligence (AI) based auto-contouring in radiation oncology has potential benefits such as standardization and time savings. However, commercial AI solutions require careful evaluation prior to clinical integration. We developed a multidimensional evaluation method to test pre-trained AI-automated contouring solutions across a network of clinics. MethodsCurated data included 121 patient planning CT (computed tomography) scans with a total of 859 clinically approved contours used for treatment from four clinics. Regions of interest (ROIs) were generated with three commercial AI-based automated contouring software solutions (AI1, AI2, AI3) spanning the following disease sites: brain, head-and-neck, thorax, abdomen, and pelvis. Quantitative agreement between AI-generated and clinical contours was measured by Dice similarity coefficient (DSC) and Hausdorff distance (HD). Qualitative assessment was performed by multiple experts scoring blinded AI-contours using a Likert scale. Workflow and usability surveying was also conducted. ResultsAI1/AI2/AI3 contours had high quantitative agreement in 27.8/32.8/34.1% of cases (DSC>0.9), performing well in pelvis (median DSC = 0.86/0.88/0.91) and thorax (median DSC = 0.91/0.89/0.91). All three solutions had low quantitative agreement in 7.4/8.8/6.1% of cases (DSC<0.5), performing worse in brain (median DSC=0.65/0.78/0.75) and H&N (median DSC=0.76/0.80/0.81). Qualitatively, AI1/AI2 contours were acceptable (rated 1-2) with at most minor edits in 70.7/74.6% of ROIs (2,906 ratings), higher for abdomen (AI1: 79.2%) and thorax (AI2: 90.2%), and lower for H&N (29.0/35.6%). An end-user survey showed strong user preference for full automation and mixed preferences for accuracy versus total number of structures generated. ConclusionOur evaluation method provided a comprehensive analysis of both quantitative and qualitative measures of commercially available pre-trained AI auto-contouring algorithms. The evaluation framework served as a roadmap for clinical integration that aligned with user workflow preference.

Multidimensional evaluation method and application based on life cycle carbon efficiency considering carbon emission, cost, and function.

Low carbon research has currently become the most discussed environmental issue. Current comprehensive evaluation methods for low carbon consider carbon emission, cost, process parameters, and resource utilization, but the realization of low carbon may lead to cost fluctuations and functional changes and lack consideration of product functional requirements. Hence, this paper developed a multidimensional evaluation method for low-carbon research based on the association among three dimensions, namely, carbon emission, cost, and function. This multidimensional evaluation method was named life cycle carbon efficiency (LCCE), which is defined as the ratio between the value in the life cycle and the carbon emissions generated. The LCCE model was established, and then carbon emission calculation, cost assessment, and function quantification of the life cycle were performed according to the three dimensions. Case study and sensitivity analysis verified the feasibility of the proposed method. The method had comprehensive and accurate evaluation results, which provided theoretical support and optimized the low-carbon design.

Optimizing ex vivo culture conditions to study human gut microbiome

The inter-individual variations of gut microbiome contribute to the different responses toward drug therapy among populations, developing a reliable ex vivo culture method for mixed bacteria is the urgent need for predicting personal reaction to drug therapy. Unfortunately, very few attentions have been paid to the bias that could be introduced during the culture process for mixed bacteria. Here we systemically evaluated the factors that may affect the outcomes of cultured bacteria from human feces. We demonstrated that inter-individual difference of host gut microbiome was the main factor affecting the outcomes of cultured bacteria, followed by the culture medium and time point. We further optimized a new medium termed GB based on our established multi-dimensional evaluation method, which could mimic the status of in situ host gut microbiome to the highest extent. Finally, we assessed the inter-individual metabolism by host gut microbiome from 10 donors on three frequently used clinical drugs (aspirin, levodopa and doxifluridine) based on the optimized GB medium. Our results revealed obvious variation in drug metabolism by microbiome from different donors, especially levodopa and doxifluridine. This work suggested the optimized culture medium had the potential for exploring the inter-individual impacts of host gut microbiome on drug metabolism.

Multi-Level Governance and Emergency Management: Building a Priority Assessment Matrix in the Pandemic Outbreak

The execution of effective responses during a large-scale emergency requires gathering appropriate information and implementing priority assessment processes. In particular, the design of comprehensive and multi-dimensional evaluation methods is crucial, especially in countries characterized by the presence of multiple levels of authority and regional governance. In this article, we illustrate the development of a structured method that was used to support emergency decisions during the COVID-19 emergency in Brazil. We applied a design science roadmap in order to produce an artifact development process, based on extensive expert involvement and multiple sources, to identify the core requirements and information needs at healthcare management and governance levels. This study provides an assessment matrix and measurement scale based on twenty indicators and five key criteria (i.e., gravity, urgency, trend, amplitude, and impact). The study provides an evidence-based method for assessing the emergency status of, and defining recommendations for, operators and policymakers. This method can be adopted for other emergency management scenarios and contexts in order to support the analysis and implementation of responses; this has a specific relevance for multi-level governance contexts.

A GIS-Based Multidimensional Evaluation Method for Solar Energy Potential in Shanxi Province, China

Solar energy is considered one of the most hopeful alternative sources to avoiding dependence on fossil fuels, and it does not cause any air pollution. GIS-based solar energy potential evaluation is mainly focused on regional scale; further, more solar energy potential evaluation with building scale is calculated through observation data and mathematical model. Therefore, in this paper, a GIS-based joint solar energy potential evaluation is developed to evaluate the distributed photovoltaic potential and centralized photovoltaic potential. Shanxi province in China, which has abundant coal resources, is used as the study area. The raster grid scale is used as the minimum research scale, which could not only deal with the distributed photovoltaic potential but could also calculate the centralized photovoltaic potential. The obtained results indicate that the developed method could effectively deal with problems associated with the distributed photovoltaic potential and centralized photovoltaic potential in the raster grid scale.

Research on the Application of AHP and Multidimensional Evaluation Method in the Integration of Expressway Construction Management Maintenance and Operation

Research on the Application of AHP and Multidimensional Evaluation Method in the Integration of Expressway Construction Management Maintenance and Operation

Sustainable Development Efficiency of Cultural Landscape Heritage in Urban Fringe Based on GIS-DEA-MI, a Case Study of Wuhan, China.

Cultural landscape heritage refers to the rare and irreplaceable cultural landscapes recognized by UNESCO and the World Heritage Committee. It is recognized as a “common works of nature and human beings” of outstanding significance and universal value, and is a type of world heritage. Dueto construction, land isincreasingly limited in urban and rural areasin the process of urbanization, and cultural landscape heritage faces a huge threat, especially larger culturallandscapeheritagelocated at the edgesof cities. However, most of the existing studies have mainly focused on the material protection of heritage but have not paid enough attention to the non-material aspects of heritage sites, failing to reveal the inseparable nature of heritage and land. Therefore, this study takes sustainable development efficiency as its analysis tool, examines two pieces of cultural landscape heritage (the Panlongcheng site and the Tomb of the King of the Ming Dynasty) in the urban edge area of Wuhan, China as examples, innovates and establishes a multidimensional evaluation method based on the GIS-DEA-Ml model, and compares the dynamic changes of the spatial development efficiency and non-spatial development efficiency of the above two cultural landscape heritage cases. The results show that: both the spatial development efficiency and non-spatial development efficiency of Panlongcheng from 2010 to 2019 are significantly higher than that of the Tomb. This method makes up for the deficiency of traditional subjective qualitative analysis. It can be used to study the development efficiency of cultural landscape heritage more objectively and comprehensively, and promote the overall sustainable development of material and intangible cultural heritage. It can provide the basis for early decision-making and post-implementation evaluation for the preservation and utilization of cultural landscape heritage under the background of urban renewal.

Multi-dimensional evaluation method for new power system

New power system that takes strong smart grid as the platform is supported by source-grid-load-storage interaction and multi-energy complementarity, because the system is green, efficient, flexible and digital. This paper focused on the research of multi-dimensional evaluation method of the new power system. Firstly, the internal and external elements of the new power system were sorted out, and KPI indicators were obtained through the analysis of the logical relationship of indicators. Secondly, this paper innovatively proposed to use “Generation Side Grid and Load” (GSGL) as the internal element and “Reliable Efficient Green and Intelligent” (REGI) as the evaluation effect. Meanwhile, this paper innovatively put forward a new multi-dimensional evaluation system of power system, with 4 secondary indicators and 16 tertiary indicators. Finally, the AAHM-weighted grey relational TOPSIS comprehensive evaluation model was constructed, and the validity and applicability of the proposed evaluation index system and model method were verified by numerical examples. Through the example analysis, under the new multi-dimensional evaluation system of power system, the comprehensive evaluation results and ranking of different provincial power enterprises were obtained. This paper provides theoretical support to further promote the transformation and upgrading of energy and electric power industry and power grid enterprises to speed up the construction of safe, reliable, green, efficient and intelligent modern power grid.

Evaluation for block-scale solar energy potential of industrial block and optimization of application strategies: A case study of Wuhan, China

Industrial blocks are an important part of the city which is very suitable for PV application because of its large-scale, unified property rights and simple form. In this study, a multi-dimensional evaluation method of solar energy potential suitable for the block-scale is constructed. Then, 48 cases of industrial blocks in a typical city of china were selected as examples. Basing on morphological parameters, all cases were classified into 7 types by clustering algorithm. Afterwards, the total amount and distribution of the solar energy potential were calculated. Finally, the strategies of the photovoltaic system application in blocks were proposed according to types of blocks. It is found that there is significant difference in solar energy potential between different types of industrial blocks. Among them, solar energy potential of single-storey types is the highest up to 90.85 kW h/m2•year, while solar energy potential of high-rise type blocks is relatively lower which is only 55.64 kW h/m2•year. In addition, block shape has obvious impact on solar energy potential, among which building density having the greatest influence, as building density increases from 20 % to 55 %, the solar energy potential also increased by 138.74 % from 42.54 kW h/m2•year to 101.56 kW h/m2•year.

Assessment of countries’ international investment activity in the context of ensuring economic security

For the vast majority of countries, creating a favorable investment environment, which determines the possibility of attracting foreign capital, is a prerequisite for economic growth, addressing issues of national interests and a sufficient level of economic security. The presented article aims to assess the development of international investment activities to ensure countries’ investment security as components of economic security. Using multidimensional evaluation methods, construction of complex indicators, methods of statistical grouping, measurement of stochastic relationships, the integrated level of investment security of Central and Eastern European countries is determined. The assessment results showed that such countries as Estonia, the Czech Republic, Latvia, Poland, Hungary, and Romania have the highest level of investment security and are among the countries that have strengthened their investment security positions over the period. The countries’ evaluation shows that 46% of the countries surveyed were classified as countries with a safe level of investment development. According to the results of correlation analysis, it was determined that the Investment Security Index is more correlated with the state of the investment climate of the country; in the group of Central and Eastern European countries, there is a close correlation with the level of investment attractiveness, which means that for these countries, macroeconomic stability and stable dynamics of socio-economic growth are the factors determining investment opportunities. The obtained results should be considered to identify the basic risks of the investment environment.

Photothermal testing of composite materials: Virtual wave concept with prior information for parameter estimation and image reconstruction

In this paper, we propose a new parameter estimation and image reconstruction approach for the photothermal testing of composite materials. Therefore, the full multidimensional evaluation method, virtual wave concept, is extended to estimate the orthotropic thermal diffusivity tensor and to reconstruct the initial temperature distribution after a laser spot heating in an orthotropic material. We establish a formal relationship between the virtual speed of sound tensor and the thermal diffusivity tensor. Furthermore, we show how prior information in the form of positivity and sparsity can be incorporated in the regularization process to improve the solution of the inverse imaging problem. In a second step, the initial temperature distribution is reconstructed by applying ultrasonic imaging methods on the calculated 3D bimodal virtual wave field. This new approach is validated on simulation and experimental data of a unidirectional carbon fiber reinforced polymer. The information loss that results from entropy production during heat diffusion can be partly compensated by including prior information. This allows an accurate parameter estimation and a high-resolution image reconstruction.

Methodology for the early analysis and evaluation of the resource efficiency of process chains for manufacturing hybrid structures

Abstract To ensure a successful development of resource-efficient and sustainable technologies, products, and production processes, it is essential to support R&D activities in early design stages. Thus, amongst others an appropriate assessment should be accomplished, which captures the high complexity and interdependencies of process chains, considers the technological feasibility, the energetic and economic benefit as well as the robustness as facets of resource efficiency, and hence, serves as a basis for deriving impulses for R&D activities. A promising evaluation methodology for such assessments is the Multidimensional Evaluation Method for Process Chains of HybrId Structures (MEMPHIS). In this paper, MEMPHIS is outlined and illustrated for an innovative process chain for producing hybrid laminates with sensor functionality. As a result, the paper will contribute to the further development of the methodology, show its applicability, and provide insights into the innovative technology.

A MULTI-DIMENSIONAL METHOD FOR EVALUATING A PRODUCT’S CONCEPTUAL SCHEMES

The use of conceptual scheme evaluation is a key step in the development of new products. In this paper, a multi-dimensional evaluation method that involves subjective evaluation, eye-tracking, and product image evaluation is established. In this study, subjective evaluation is used to test customers’ initial reactions to conceptual schemes, and eye- tracking is used to highlight the features of conceptual schemes that are most attractive to customers. With the help of Kansei engineering, the most attractive features of a particular product are described and clarified from the product image evaluation. This multi- dimensional method can be applied not only in screening conceptual schemes, but also in exploring the reasons and suggestions for product improvement. The method was assessed in this study through a case study evaluation of conceptual design schemes for a mobile phone.

Does Arts Education Develop School Readiness? Teachers’ and Artists’ Points of View on an Art Education Project

More than 98 percent of children in Finland attend preschool, where different kinds of projects are carried out in order to strengthen the children's abilities. This article focuses on the effects of one arts education project from a school readiness point of view. The main question was, How did the Helsinki arts education project affect the children's learning skills and attitudes? The target groups were children aged three to nine years who participated in the arts project in day care centers and schools. A multidimensional evaluation method was used for the analyses. The research data consisted of interviews of the program artists and educators (n = 23), follow-up reports (n = 9), and other materials. The results show that the program motivated children and aroused their interest in thinking, problem-solving, practicing, and learning. It offered children opportunities to experience success, which increased their self-confidence and skills. The project also strengthened their abilities in listening, goal-oriented work, evaluating others’ work, and receiving feedback, which are all abilities required for school entrance. The subject matter of their school courses was also integrated into their achievements.